Mapping_AS_cases in Montreal

library(ggplot2)
library(magrittr)
library(dplyr)
library(plotly)
case_final_map<-readRDS('case_map.RData')
interv_final_map<-readRDS('interv_map.RData')

This plots shows incidence rate of aortic stenosis (per 1000 person year above 65) in Montreal between 2000 and 2010. City of Montreal was divided by CLSC regions. The number of incidence cases were ascertained from in-hospital diagnosis of aortic stenosis from RAMQ database.

The incidence rate were calculated as: \(\frac{Cumulative\:number\:of\:incidence\:AS\:cases}{Mean\: population >=65 * 10 years}\)

p<-ggplot(data=case_final_map,aes(long,lat,group=group,fill=rate,label=CLSC_nom)) + 
  geom_polygon(color='gray70',size=0.2)+
  #coord_map(projection='albers',lat0=39,lat1=45)+
  theme(axis.line=element_blank(),
        axis.text=element_blank(),
        axis.ticks=element_blank(),
        axis.title=element_blank(),
        panel.background=element_blank(),
        panel.border=element_blank(),
        panel.grid=element_blank(),
        panel.spacing=unit(0, "lines"),
        plot.background=element_blank(),
        legend.justification = c(0.9,0.2),
        legend.position = c(0.95,0.2)
  )#+facet_wrap(~cyear)

p<- p+scale_fill_gradient(low='slategray1', high='royalblue4')
 #default color is set to blue, can be set
ggplotly(p)%>%layout(title='Incidence rate of AS in Montreal \n from 2000-2010',
                       titlefont=list(size=15))

This plots shows the rate of surgical valve replacement(per 1000 person year above 65) performed in Montreal between 2000 and 2010. City of Montreal was divided by CLSC regions.The number of SAVRs were ascertained from in-hospital interventions from RAMQ database.

The rate of SAVR were calculated as: \(\frac{Cumulative\:number\:of\:SAVR}{Mean\:population >=65 * 10 years}\)

p<-ggplot(data=interv_final_map,aes(long,lat,group=group,fill=rate,label=CLSC_nom)) + 
  geom_polygon(color='gray70',size=0.2)+
  #coord_map(projection='albers',lat0=39,lat1=45)+
  theme(axis.line=element_blank(),
        axis.text=element_blank(),
        axis.ticks=element_blank(),
        axis.title=element_blank(),
        panel.background=element_blank(),
        panel.border=element_blank(),
        panel.grid=element_blank(),
        panel.spacing=unit(0, "lines"),
        plot.background=element_blank(),
        legend.justification = c(0.9,0.2),
        legend.position = c(0.95,0.2)
  )#+facet_wrap(~cyear)

p<- p+scale_fill_gradient(low='slategray3', high='royalblue4')
ggplotly(p)%>%layout(title='Rate of SAVR in Montreal \n from 2000-2010',
                       titlefont=list(size=15))

p<-ggplot(data=case_final_map,aes(long,lat,group=group,fill=mean_pop,label=CLSC_nom)) + 
  geom_polygon(color='gray70',size=0.2)+
  #coord_map(projection='albers',lat0=39,lat1=45)+
  theme(axis.line=element_blank(),
        axis.text=element_blank(),
        axis.ticks=element_blank(),
        axis.title=element_blank(),
        panel.background=element_blank(),
        panel.border=element_blank(),
        panel.grid=element_blank(),
        panel.spacing=unit(0, "lines"),
        plot.background=element_blank(),
        legend.justification = c(0.9,0.2),
        legend.position = c(0.95,0.2)
  )#+facet_wrap(~cyear)

p<- p+scale_fill_gradient(low='yellow', high='red')
 #default color is set to blue, can be set
ggplotly(p)%>%layout(title='Average population >=65 years old in Montreal \n from 2000-2010',
                       titlefont=list(size=15))